> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompts in Code

> Pull and push prompt changes via Phoenix's Python and TypeScript Clients

<Frame caption="Pull and push prompt changes via Phoenix's Python and TypeScript Clients">
  <img src="https://storage.googleapis.com/arize-phoenix-assets/assets/images/phoenix-docs-images/c385cf9f-image.jpeg" />
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Using Phoenix as a backend, Prompts can be managed and manipulated via code by using our Python or TypeScript SDKs.

With the Phoenix Client SDK you can:

* [Create / Update](/docs/phoenix/prompt-engineering/how-to-prompts/create-a-prompt#using-the-phoenix-client) prompts dynamically

* [Pull prompts](/docs/phoenix/prompt-engineering/how-to-prompts/using-a-prompt) templates by name, version, or tag

* [Format prompt](/docs/phoenix/prompt-engineering/how-to-prompts/using-a-prompt#using-a-prompt) templates with runtime variables and use them in your code. Native support for OpenAI, Anthropic, Gemini, Vercel AI SDK, and more. No propriatry client necessary.

* Support for [tool calling](/docs/phoenix/prompt-engineering/concepts-prompts/prompts-concepts#tools) and [response formats](/docs/phoenix/prompt-engineering/concepts-prompts/prompts-concepts#response-format). Execute tools defined within the prompt. Phoenix prompts encompasses more than just the text and messages.

To learn more about managing Prompts in code, see [Using a prompt](/docs/phoenix/prompt-engineering/how-to-prompts/using-a-prompt)